GSA: further simplification related to qmc_sequence

matlab/gsa/lptauSEQ.m

-function [lpmat] = lptauSEQ(Nsam,Nvar)
-
-% [lpmat] = lptauSEQ(Nsam,Nvar)
-%
-% Generates a sample from a sobol sequence of length Nsam for a
-% number of parameters Nvar
-%
-% Copyright (C) 2005 Marco Ratto
-% THIS PROGRAM WAS WRITTEN FOR MATLAB BY
-% Marco Ratto,
-% Unit of Econometrics and Statistics AF
-% (http://www.jrc.cec.eu.int/uasa/),
-% IPSC, Joint Research Centre
-% The European Commission,
-% TP 361, 21020 ISPRA(VA), ITALY
-% marco.ratto@jrc.it 
-%
-
-
-clear lptau
-lpmat = zeros(Nsam, Nvar);
-seed = int64(0);
-for j=1:Nsam,
-    [v, seed] = qmc_sequence(Nvar, seed, 0);
-    lpmat(j,:) = v;
-end
-return

matlab/gsa/stab_map_.m

@@ -28,8 +28,7 @@ function x0 = stab_map_(OutputDirectoryName)
 % 3) Bivariate plots of significant correlation patterns
 %  ( abs(corrcoef) > alpha2) under the stable and unacceptable subsets
 %
-% USES lptauSEQ,
-%      stab_map_1, stab_map_2
+% USES qmc_sequence, stab_map_1, stab_map_2
 %
 % Part of the Sensitivity Analysis Toolbox for DYNARE
 %
@@ -118,7 +117,7 @@ if fload==0,
         Nsam=size(lpmat,1);
     else
         if np<52 & ilptau>0,
-            [lpmat] = lptauSEQ(Nsam,np); % lptau
+            [lpmat] = qmc_sequence(np, int64(0), 0, Nsam)';
             if np>30 | ilptau==2, % scrambled lptau
                 for j=1:np,
                     lpmat(:,j)=lpmat(randperm(Nsam),j);